Legacy systems accumulate debt in layers. A patch here to keep a service running. A workaround there because the right fix would take too long. A testing environment that drifted away from production months ago and was never corrected. Individually, each decision was reasonable. Collectively, they compound into something that slows every team down and makes every change feel riskier than it should.
This real estate information and analytics company had reached that point. The infrastructure was aging, spread across a mix of on-premises and early cloud environments that lacked consistency and automated management. The testing processes were heavily manual, which meant coverage was uneven and deployments carried more uncertainty than the team was comfortable with. The technical debt was real, the operational burden was growing, and the cost of the status quo was becoming harder to justify.
The challenge was to fix it at scale, without a runaway budget, and in a way that left the team genuinely capable of maintaining and extending what was built.
Shift-Left Testing and Development Modernization
Testing was addressed first because it touched every other part of the modernization. Manual verification processes were causing bottlenecks, and the test suite the team had accumulated was unreliable enough that passing tests did not reliably indicate working software. This is a common pattern in organizations that have added testing incrementally without a coherent strategy, and it requires more than just adding automation.
VergeOps promoted shift-left practices that moved quality concerns earlier in the development cycle, where defects are far cheaper to identify and fix. Testing environments were unified and brought into alignment with production configurations. Manual testers were transitioned to code-based automation, leveraging AI tooling where it accelerated the work, with a focus on building a suite the team could trust and maintain rather than one that existed on paper.
The goal was not just to have more automated tests. It was to have tests that actually reflected the system’s behavior accurately enough that a green pipeline meant something. Getting there required both technical work and a change in how the team thought about quality as part of the development process rather than a phase after it.
Infrastructure Modernization at Scale
The infrastructure work was substantial. More than 500 databases were migrated to AWS, a program that required careful sequencing, data validation, and rollback planning at every step. More than 30 applications were containerized, which involved not just packaging but also revising how those applications handled configuration, secrets, and environment-specific behavior.
Legacy environments were transitioned to Kubernetes with Istio for service mesh capabilities and Terraform as the infrastructure-as-code backbone. This gave the team infrastructure that was version-controlled, reproducible, and auditable rather than a collection of manual steps that lived in runbooks and institutional memory.
What We Built
Testing Modernization
Shift-left practices, unified testing environments, and a transition from manual verification to reliable code-based automation. Manual testers upskilled to write and maintain automated suites, with AI tooling used to accelerate where appropriate.
Database and Application Migration
500+ databases migrated to AWS with careful sequencing and validation. 30+ applications containerized with proper handling of configuration, secrets, and environment-specific behavior.
Modern Infrastructure Platform
Legacy environments transitioned to Kubernetes with Istio for service mesh and Terraform for infrastructure-as-code. Version-controlled, reproducible infrastructure that the team could operate, extend, and audit without relying on manual runbooks or institutional memory.
The Outcome
The infrastructure is modernized, the testing processes are reliable, and the team owns what was built. That last point matters more than it might seem. The engagement was designed from the start to build internal capability rather than create ongoing dependency. The engineers who worked alongside the VergeOps team throughout the program came out the other side with the knowledge and confidence to maintain and extend everything delivered.
The cost model was notable as well. The full scope of the engagement, across infrastructure migration, application containerization, testing modernization, and team enablement, was delivered at less than half the cost of a single entry-level full-time employee. That ratio reflects the efficiency of bringing in a specialized team for a scoped program rather than trying to staff and ramp permanent headcount for a one-time modernization effort.
Facing a Similar Challenge?
Large-scale modernization programs that span infrastructure, testing, and team capability require experience across all three dimensions at once. VergeOps brings the technical depth and the coaching approach to deliver meaningful change efficiently and build the internal capability to sustain it.